Product Information

Description

An annual survey of the cs.CY arXiv category, covering research published from September 2025 – August 2026. Built on a close-reading set of 144 papers and organised into 40 chapters, it maps the year by the field's research sub-directions.

Book framework (share of the year's output):

AI Governance, Safety, and Sociotechnical Risk (17.1%) — Addresses frameworks for AI governance, incident reporting, and sociotechnical safety risks in deployed systems.
AI in Education and Academic Integrity (16.6%) — Examines the integration of AI in higher education, student privacy, and challenges to academic integrity.
Large Language Model Bias and Value Alignment (11.9%) — Investigates demographic and value biases in large language models and methods for evaluating their alignment.
LLM Agents and Synthetic Persona Evaluation (8.3%) — Focuses on the behavior, bias, and real-world impact of LLM-based agents and synthetic personas.
Generative AI Epistemic Impact and Trust (7.9%) — Analyzes the erosion of trust, information verification challenges, and epistemic risks posed by generative AI.
Human-AI Interaction and Cognitive Collaboration (6.9%) — Explores human-AI collaboration frameworks, cognitive alignment, and the impact of AI on human decision-making.
Algorithmic Fairness and Machine Learning Ethics (6.7%) — Develops techniques for ensuring fairness, reducing bias, and implementing ethical constraints in machine learning models.
Data Privacy, Protection, and Digital Rights (6.4%) — Addresses privacy laws, data protection frameworks, and the ethical use of data in smart systems and gig economies.
Social Media Dynamics and Online Behavior (6.0%) — Studies online toxicity, polarization, mental health impacts, and user behavior on social media platforms.
AI Systems Design and Multi-Agent Frameworks (4.9%) — Proposes architectural frameworks for multi-agent systems, digital twins, and AI certification standards.
Socio-Technical Evaluation and Moral Reasoning (3.8%) — Evaluates AI systems through socio-technical lenses, focusing on moral reasoning, legal liability, and cultural affordances.
Broad Societal Impacts of Artificial Intelligence (3.5%) — Discusses macro-level societal challenges including intellectual property, workforce adaptation, and sustainable AI.

Each sub-direction is covered across three chapters — how it framed its questions, the strength of its key findings, and its open debates and frontiers — so the reader gets a traceable picture of what this part of the field actually produced over the year.